The present invention relates to autonomous vehicle networks, and more specifically, to the integration of human-controlled vehicles into an autonomous vehicle network through automatic driver modeling.
As vehicle transportation networks transform from roadways used by vehicles controlled almost entirely by human drivers into roadways for autonomous vehicles controlled wholly by onboard and remote servers, an interim period will occur when roads must be shared by both autonomous and human-controlled vehicles. Autonomous vehicles rely on a combination of inputs from onboard sensors, vehicle control computing resources, and communications between vehicles, and from remote servers engaged in, for example, scheduling of vehicle traffic and alerting autonomous vehicles of conditions that cannot be sensed or communicated locally.
Both interactions and communications between vehicles and with remote servers require standard autonomous interfaces between autonomous vehicles, their onboard sensors and control mechanisms, and the computing resources of other vehicles and remote servers. These interfaces may communicate details such as vehicle location, speed, and subsequent actions, which then allows other vehicles to plan their own actions and remote servers to schedule and control the actions of groups of vehicles effectively. Without these standard autonomous interfaces, communications between vehicles must be through onboard sensors and processed locally in the time available, much as a human relies on local biological sensors to control a vehicle.